The document provides a practical guide on querying and visualizing linked open data using the eea.daviz product. It explains the principles of open data and linked data and demonstrates various SPARQL query examples for retrieving data from sources like DBpedia and Enipedia. Additionally, it highlights how to create data visualizations in a short time, showcasing the capabilities of the eea.daviz platform.

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Visualize open data with Plone - eea.daviz PLOG 2013

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  Visualizing Open Datawith Plonea practical guide on how to query and visualize Linked Open Data with eea.daviz product Antonio De Marinis Web Technology Management European Environment Agency www.eea.europa.eu
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  Linked Data evolution 2007 as per 2011 keeps growing... > 1 million datasets Watch video STRATA conference 2013
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  Open Data -what is it? Open data is a philosophy and practice requiring that certain data be freely available to everyone, without restrictions from copyright, patents or other mechanisms of control. Linked Open Data (LOD) or simply Linked Data is a technique to interlink all open datasets into a web of data, aka semantic web, using technologies like RDF and SPARQL.
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  Linked Data vsclassic ODBC
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  SPARQL query structureA SPARQL query comprises, in order: ● Prefix declarations, for abbreviating URIs ● Dataset definition, stating what RDF graph(s) are being queried ● A result clause, identifying what information to return from the query ● The query pattern, specifying what to query for in the underlying dataset ● Query modifiers, slicing, ordering, and otherwise rearranging query results # prefix declarations PREFIX foo: <http://example.com/resources/> ... # dataset definition FROM ... # result clause SELECT ... # query pattern WHERE { ... } # query modifiers ORDER BY ...
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  Real example queryingDBpediaSELECT * WHERE {?subject rdf:type <http://dbpedia.org/ontology/City>.?subject rdfs:label ?label.?subject rdfs:comment ?abstract.?subject <http://dbpedia.org/ontology/populationTotal> ?populationTotal.FILTER (lang(?label) = "en" && lang(?abstract) = "en")} LIMIT 5
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  Let's dive intoa real example SELECT * WHERE { ?subject rdf:type <http://dbpedia.org/ontology/City>. ?subject rdfs:label ?label. ?subject rdfs:comment ?abstract. ?subject <http://dbpedia.org/ontology/populationTotal> ?populationTotal. FILTER (lang(?label) = "en" && lang(?abstract) = "en" && (?populationTotal >= "5000000"^^xsd: integer)) } LIMIT 5
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  Let's dive intoa real example PREFIX o: <http://dbpedia.org/ontology/> PREFIX p: <http://dbpedia.org/property/> PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#> PREFIX geo: <http://www.w3.org/2003/01/geo/wgs84_pos#> SELECT DISTINCT * WHERE { ?subject a o:City. ?subject rdfs:label ?label. OPTIONAL {?subject rdfs:comment ?abstract.} ?subject p:populationTotal ?populationTotal. OPTIONAL {?subject geo:lat ?latitude.} OPTIONAL {?subject geo:long ?longitude.} FILTER (lang(?label) = "en" && lang(?abstract) = "en" && (?populationTotal >= "5000000"^^xsd:integer && ?populationTotal < "60000000"^^xsd:integer)) } ORDER BY DESC(?populationTotal) find all properties by exploring dbpedia e.g. dbpedia http://dbpedia.org/page/Tokyo Example without duplicates http://daviz.eionet. europa.eu/data/local-sparql-queries/most- populated-cities
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  Corresponding data visualisationwithDaviz We have been able to create a data visualisation of open linked data with filters/facets entirely through the web in about 10 minutes! live demo http://www.eea.europa.eu/sandbox/plog2013/most-populated-cities- with-coordinates-plus
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  Removing redundanciesTIP: Inorder to get rid of some rednundancy you can use "SAMPLE" or "SELECT DISTINCT"PREFIX o: <http://dbpedia.org/ontology/>PREFIX p: <http://dbpedia.org/property/>PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>PREFIX geo: <http://www.w3.org/2003/01/geo/wgs84_pos#>SELECT ?subject (sql:SAMPLE(?subject) as ?city)(sql:SAMPLE(?label) as ?label)(sql:SAMPLE(?latitude) as ?latitude) live example http://daviz.eionet.europa.(sql:SAMPLE(?longitude) as ?longitude) max(?populationTotal) as ?maxPopulation eu/visualisations/most-populated-cities max(?rainyDays) as ?rainyDaysWHERE {?subject a o:City.?subject rdfs:label ?label.OPTIONAL {?subject rdfs:comment ?abstract.}?subject p:populationTotal ?populationTotal.OPTIONAL {?subject geo:lat ?latitude.}OPTIONAL {?subject geo:long ?longitude.}OPTIONAL {?subject p:yearPrecipitationDays ?rainyDays.}FILTER (lang(?label) = "en" && lang(?abstract) = "en" && (?populationTotal >= "5000000"^^xsd:integer))}GROUP BY ?subjectORDER BY DESC(?maxPopulation)
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  More examples atDaviz show room daviz.eionet.europa.eu
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  Example 2: Largecompanies (DBpedia) PREFIX o: <http://dbpedia.org/ontology/> PREFIX p: <http://dbpedia.org/property/> PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#> PREFIX geo: <http://www.w3.org/2003/01/geo/wgs84_pos#> SELECT * WHERE { ?subject rdf:type <http://dbpedia.org/ontology/Company>. ?subject rdfs:label ?label. ?subject rdfs:comment ?abstract. ?subject p:numEmployees ?employees. ?subject o:location ?location. ?location geo:lat ?latitude. ?location geo:long ?longitude. FILTER (lang(?label) = "en" && lang(?abstract) = "en" && ?employees > 10000) } ORDER BY DESC(?employees) LIMIT 20
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  Example 3: Energyplants (Enipedia) SPARQL Endpoint:http://enipedia.tudelft.nl/sparql BASE <http://enipedia.tudelft.nl/wiki/> PREFIX a: <http://enipedia.tudelft.nl/wiki/> PREFIX prop: <http://enipedia.tudelft.nl/wiki/Property:> PREFIX cat: <http://enipedia.tudelft.nl/wiki/Category:> PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#> PREFIX rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> select ?Name ?Point ?Generation_capacity where { ?powerPlant prop:Country a:Italy . ?powerPlant rdfs:label ?Name . ?powerPlant prop:Point ?Point . ?powerPlant prop:Generation_capacity_electrical_MW ?Generation_capacity . }
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  More resources ● SPARQL endpoints and their status: http://labs.mondeca. com/sparqlEndpointsStatus/index.html ● SPARQL tutorial by example: http://www.cambridgesemantics.com/semantic- university/sparql-by-example ● eea.sparql package gives you a sparql client and data holder for plone available on pypi ● eea.daviz bundle includes eea.sparql and the visualisations tools
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  Data table manipulationvia drag and drop
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  Modular framework
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  EEA Daviz And much more...
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  EEA Daviz Live Demo
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  EEA Daviz -ResourcesMore live examples ○ Eionet http://daviz.eionet.europa.eu ○ EEA http://www.eea.europa.eu/data-and-maps/daviz